Towards machines that know when they do not know: Summary of work done at 2014 Frederick Jelinek Memorial Workshop
Hynek Heřmanský, Lukáš Burget, Jordan R. Cohen, Emmanuel Dupoux, Naomi H. Feldman, John J. Godfrey, Sanjeev P. Khudanpur, Matthew Maciejewski, Sri Harish Mallidi, Anjali Menon, Tetsuji Ogawa, Vijayaditya Peddinti, Richard Cameron Rose, Richard M. Stern, Matthew Wiesner, Karel Veselý · 2015
A group of junior and senior researchers gathered as a part of the 2014 Frederick Jelinek Memorial Workshop in Prague to address the problem of predicting the accuracy of a nonlinear Deep Neural Network probability estimator for unknown data in a different application domain from the domain in which the estimator was trained. The paper describes the problem and summarizes approaches that were taken by the group1.